The present invention relates to wireless communication, and, more particularly, to a method for improving multiuser MIMO downlink transmission.
In the multi-input multi-output (MIMO) broadcast channel, also referred to as the downlink (DL) multiuser MIMO (MU-MIMO) channel, different data streams can be transmitted via transmit antenna arrays to multiple receivers through the same channel resources. The sum throughput can be significantly increased due to the multiuser diversity. It has been shown that the capacity of multiuser broadcast channel can be achieved with dirty paper coding (DPC). However, although DPC can be implemented based on vector quantizers and powerful channel codes (e.g., low-density parity-check codes or turbo codes), the extremely high complexity makes it infeasible to be implemented in practical cellular systems. Therefore, the suboptimal linear transmit precoding techniques are of great interests for DL MU-MIMO due to their much lower complexity compared with DPC. It is shown that when perfect channel state information (CSI) is available at the base station, the linear transmit precoding performs very close to DPC for MIMO broadcast channel. Hence, the MU-MIMO with low-complexity linear precoding has been included in the new cellular standards, e.g., the emerging 3GPP Long Term Evolution Advanced (LTE-A) and IEEE 802.16m.
However, in practical FDD cellular systems, only the quantized channel information can be reported from each active user to the serving base station. Such imperfect channel information causes severe performance degradation when MU-MIMO is dynamically scheduled as a transmission mode at the base station. For instance, in the 3GPP LTE-A standard, each active user reports a preferred matrix index (PMI) to the base station, which is an index that identifies either a particular vector in a codebook of unit norm vectors or a particular matrix in a codebook of semi-unitary matrices. The codebooks are known in advance to the base station as well as all users. Each user also reports one or more channel quality indices (CQIs) (per sub-band) which are its quantized estimates of the signal-to-interference-plus-noise ratios (SINRs). Since these CQIs can be directly mapped by the base station to certain SINRs via look-up-tables, we will refer to the latter SINRs as the SINRs contained in the user's CSI report or as SINRs of the CSI report. The reported PMIs and CQIs are then employed by the base station to determine a suitable set of scheduled users, their transmit precoders and assigned rates. In 3GPP LTE standard, the reported PMIs and CQIs are based on the assumption of the single user (SU) MIMO transmissions. While such quantized SU channel reports are sufficient for the link adaptation in SU-MIMO transmission, for MU-MIMO transmissions, such SU report results in a large mismatch between the channel SINR feedback and the actual SINR that the user sees after being scheduled. To alleviate this problem, the quantized channel feedback assuming MU-MIMO is proposed in to mitigate the SINR mismatch and enhance the performance of MU-MIMO. Other similar schemes aiming to improve the CQI accuracy for MU-MIMO have been actively investigated in the 3GPP LTE-A standards.
On the other hand, in a cellular system, users are usually asymmetric due to their different locations in a cell, i.e., different distances from the base station. Some user's channel can be much stronger than that of another user's, thus allowing it to enjoy a higher average throughput. To exploit multiuser diversity gains while achieving fair resource allocation among all serviced users, the proportional fair (PF) scheduling is a preferred approach which uses the sum of the normalized (or weighted) instantaneous user rates as the scheduling metric. However, for MU-MIMO such weighted sum rate metric brings some problems since the PF scheduling itself is sensitive to the accuracy of the available CSI and hence exacerbates the SINR mismatch problem, particularly when a user with a low average SNR is scheduled in a MU-MIMO transmission mode.
Among prior art techniques, there has been disclosed a method whereby an outer loop link adaptation (OLLA) is employed based on the transmission acknowledgement (ACK/NACK based) to improve the rate matching accuracy.
Applicants consider a downlink (DL) multiuser (MU) multi-input-multi-output (MIMO) channel with linear procoding where the base station schedules several user terminals on the same frequency sub-band the imperfect channel state information at the base station, e.g., the quantized channel feedback report. Among two types of channel state information (CSI) reports from user terminals, i.e., the CSI report that assumes the single-user (SU) MIMO transmissions and the enhanced CSI feedback that assumes the MU-MIMO transmissions. A large SINR mismatch is observed between the SINR feedback and the actual SNR that the user sees after being scheduled if MU-MIMO is scheduled with only the SU CSI report available or the SU-MIMO is scheduled with only the MU CSI report available at the base station. The SINR mismatch affects the rate matching accuracy which degrades overall system throughput. On the other hand, the MU-MIMO gain over SU-MIMO is only significant in the high SNR region. However, with the proportional fair (PF) scheduling which is commonly used in the commercial cellular system, the user with low SINR can be scheduled for MU-MIMO transmissions which not only reduce the MU-MIMO performance gain but also could hurt the overall system performance when SINR mismatch is involved.
Accordingly, there is a need for improved multiuser MIMO downlink transmission.